Development of New Materials for Optically Programmable and Re-Programmable Printable Memristors for Neuromorphic Computing
Development of New Materials for Optically Programmable and Re-Programmable Printable Memristors for Neuromorphic Computing
批准号:
2853290
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2022
资助国家:
英国
项目状态:
未结题
起止时间:
2022 至 --
中文摘要
印刷电子学(即使用添加的低温印刷工艺制造电子设备和电路的技术)承诺以新的形状因数(例如,在柔性或共形衬底上)在大面积范围内以低成本、按需制造电子电路。最有希望的商业机会是智能传感器、智能标签和可穿戴设备,这些领域的智能处理都嵌入了设备中。这些系统的交付需要低功率、低成本和低组件数量的模拟计算,并结合深度学习算法,这导致了对模拟神经网络计算的兴趣的重新燃起,有时被称为“神经形态”计算方法。硬件的关键部件需要新的材料来提供必要的坚固、可编程和可打印的设备。该研究项目的重点是开发新的有机半导体,其中材料的电阻能够通过沉积成薄膜后暴露在可见光下进行编程和重新编程。材料电阻的这种光学编码对于分离忆阻器器件中的写入和读取过程以及为神经形态电路提供稳定、坚固和可重现的可编程元件是重要的。该项目涉及有机合成、分子表征(包括光学光谱)、电子结构计算、油墨配方、薄膜印刷、薄膜表征、器件制造和测试。将材料和设备集成到电路中将在曼彻斯特大学的电子和电气工程系进行。
英文摘要
Printed electronics (i.e. the technology of fabricating electronic devices and circuits using additive, low-temperature printing processes) promises low-cost, on-demand electronic circuit fabrication, in new form-factors (e.g. on flexible or conformal substrates) using bio-compatible components, over large areas. The most promising commercial opportunities are in intelligent sensors, smart tags and wearables, where intelligent processing is embedded in the device. Delivery of these systems requires the low-power, low-cost, and low component count of analogue computing, combined with deep learning algorithms and this has led to a resurgence of interest in analogue neural network computing, sometimes termed a "neuromorphic" approach to computation. Critical components of the hardware require new materials to deliver the necessary robust, programmeable and printable devices. This research project focusses on the development of new organic semiconductors in which the resistance of the material is capable of being programmed and re-programmed by exposure to visible light after deposition into a thin film. This optical encoding of the materials resistance is important to decouple the write and read processes in memristor devices and to deliver stable, robust and reproducible progammeable elements for neuromorphic circuits. The project involves organic synthesis, molecular characterisation including optical spectroscopy, calculation of electronic structure, formulation of inks, printing of thin films, thin film characterisation, device fabrication and testing. Integration of the materials and devices into circuits will be carried out in the Department of Electronics and Electrical Engineering at The University of Manchester.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
海外基金